Stability of spectro-temporal tuning over several seconds in primary auditory cortex of the awake ferret

Auditory cortex shapes sound responses in the inferior colliculus

The extensive feedback from the auditory cortex (AC) to the inferior colliculus (IC) supports critical aspects of auditory behavior but has not been extensively characterized. Previous studies demonstrated that activity in IC is altered by focal electrical stimulation and pharmacological inactivation of AC, but these methods lack the ability to selectively manipulate projection neurons. We measured the effects of selective optogenetic modulation of cortico-collicular feedback projections on IC sound responses in mice. Activation of feedback increased spontaneous activity and decreased stimulus selectivity in IC, whereas suppression had no effect. To further understand how microcircuits in AC may control collicular activity, we optogenetically modulated the activity of different cortical neuronal subtypes, specifically parvalbumin-positive (PV) and somatostatin-positive (SST) inhibitory interneurons. We found that modulating the activity of either type of interneuron did not affect IC sound-evoked activity. Combined, our results identify that activation of excitatory projections, but not inhibition-driven changes in cortical activity, affects collicular sound responses.

Gain Control in the Auditory Cortex Evoked by Changing Temporal Correlation of Sounds

Natural sounds exhibit statistical variation in their spectrotemporal structure. This variation is central to identification of unique environmental sounds and to vocal communication. Using limited resources, the auditory system must create a faithful representation of sounds across the full range of variation in temporal statistics. Imaging studies in humans demonstrated that the auditory cortex is sensitive to temporal correlations. However, the mechanisms by which the auditory cortex represents the spectrotemporal structure of sounds and how neuronal activity adjusts to vastly different statistics remain poorly understood. In this study, we recorded responses of neurons in the primary auditory cortex of awake rats to sounds with systematically varied temporal correlation, to determine whether and how this feature alters sound encoding. Neuronal responses adapted to changing stimulus temporal correlation. This adaptation was mediated by a change in the firing rate gain of neuronal responses rather than their spectrotemporal properties. This gain adaptation allowed neurons to maintain similar firing rates across stimuli with different statistics, preserving their ability to efficiently encode temporal modulation. This dynamic gain control mechanism may underlie comprehension of vocalizations and other natural sounds under different contexts, subject to distortions in temporal correlation structure via stretching or compression.

Stable encoding of sounds over a broad range of statistical parameters in the auditory cortex

Natural auditory scenes possess highly structured statistical regularities, which are dictated by the physics of sound production in nature, such as scale‐invariance. We recently identified that natural water sounds exhibit a particular type of scale invariance, in which the temporal modulation within spectral bands scales with the centre frequency of the band. Here, we tested how neurons in the mammalian primary auditory cortex encode sounds that exhibit this property, but differ in their statistical parameters. The stimuli varied in spectro‐temporal density and cyclo‐temporal statistics over several orders of magnitude, corresponding to a range of water‐like percepts, from pattering of rain to a slow stream. We recorded neuronal activity in the primary auditory cortex of awake rats presented with these stimuli. The responses of the majority of individual neurons were selective for a subset of stimuli with specific statistics. However, as a neuronal population, the responses were remarkably stable over large changes in stimulus statistics, exhibiting a similar range in firing rate, response strength, variability and information rate, and only minor variation in receptive field parameters. This pattern of neuronal responses suggests a potentially general principle for cortical encoding of complex acoustic scenes: while individual cortical neurons exhibit selectivity for specific statistical features, a neuronal population preserves a constant response structure across a broad range of statistical parameters.

Spike timing precision changes with spike rate adaptation in the owl's auditory space map

Spike rate adaptation (SRA) is a continuing change of responsiveness to ongoing stimuli, which is ubiquitous across species and levels of sensory systems. Under SRA, auditory responses to constant stimuli change over time, relaxing toward a long-term rate often over multiple timescales. With more variable stimuli, SRA causes the dependence of spike rate on sound pressure level to shift toward the mean level of recent stimulus history. A model based on subtractive adaptation (Benda J, Hennig RM. J Comput Neurosci 24: 113-136, 2008) shows that changes in spike rate and level dependence are mechanistically linked. Space-specific neurons in the barn owl's midbrain, when recorded under ketamine-diazepam anesthesia, showed these classical characteristics of SRA, while at the same time exhibiting changes in spike timing precision. Abrupt level increases of sinusoidally amplitude-modulated (SAM) noise initially led to spiking at higher rates with lower temporal precision. Spike rate and precision relaxed toward their long-term values with a time course similar to SRA, results that were also replicated by the subtractive model. Stimuli whose amplitude modulations (AMs) were not synchronous across carrier frequency evoked spikes in response to stimulus envelopes of a particular shape, characterized by the spectrotemporal receptive field (STRF). Again, abrupt stimulus level changes initially disrupted the temporal precision of spiking, which then relaxed along with SRA. We suggest that shifts in latency associated with stimulus level changes may differ between carrier frequency bands and underlie decreased spike precision. Thus SRA is manifest not simply as a change in spike rate but also as a change in the temporal precision of spiking.

A new and fast characterization of multiple encoding properties of auditory neurons

The functional properties of auditory cortex neurons are most often investigated separately, through spectrotemporal receptive fields (STRFs) for the frequency tuning and the use of frequency sweeps sounds for selectivity to velocity and direction. In fact, auditory neurons are sensitive to a multidimensional space of acoustic parameters where spectral, temporal and spatial dimensions interact. We designed a multi-parameter stimulus, the random double sweep (RDS), composed of two uncorrelated random sweeps, which gives an easy, fast and simultaneous access to frequency tuning as well as frequency modulation sweep direction and velocity selectivity, frequency interactions and temporal properties of neurons. Reverse correlation techniques applied to recordings from the primary auditory cortex of guinea pigs and rats in response to RDS stimulation revealed the variety of temporal dynamics of acoustic patterns evoking an enhanced or suppressed firing rate. Group results on these two species revealed less frequent suppression areas in frequency tuning STRFs, the absence of downward sweep selectivity, and lower phase locking abilities in the auditory cortex of rats compared to guinea pigs.

Rapid spectrotemporal plasticity in primary auditory cortex during behavior

Complex natural and environmental sounds, such as speech and music, convey information along both spectral and temporal dimensions. The cortical representation of such stimuli rapidly adapts when animals become actively engaged in discriminating them. In this study, we examine the nature of these changes using simplified spectrotemporal versions (upward vs downward shifting tone sequences) with domestic ferrets (Mustela putorius). Cortical processing rapidly adapted to enhance the contrast between the two discriminated stimulus categories, by changing spectrotemporal receptive field properties to encode both the spectral and temporal structure of the tone sequences. Furthermore, the valence of the changes was closely linked to the task reward structure: stimuli associated with negative reward became enhanced relative to those associated with positive reward. These task- and-stimulus-related spectrotemporal receptive field changes occurred only in trained animals during, and immediately following, behavior. This plasticity was independently confirmed by parallel changes in a directionality function measured from the responses to the transition of tone sequences during task performance. The results demonstrate that induced patterns of rapid plasticity reflect closely the spectrotemporal structure of the task stimuli, thus extending the functional relevance of rapid task-related plasticity to the perception and learning of natural sounds such speech and animal vocalizations.

Component analysis reveals sharp tuning of the local field potential in the guinea pig auditory cortex

Local field potentials (LFPs) recorded in the auditory cortex of mammals are known to reveal weakly selective and often multimodal spectrotemporal receptive fields in contrast to spiking activity. This may in part reflect the wider "listening sphere" of LFPs relative to spikes due to the greater current spread at low than high frequencies. We recorded LFPs and spikes from auditory cortex of guinea pigs using 16-channel electrode arrays. LFPs were processed by a component analysis technique that produces optimally tuned linear combinations of electrode signals. Linear combinations of LFPs were found to have sharply tuned responses, closer to spike-related tuning. The existence of a sharply tuned component implies that a cortical neuron (or group of neurons) capable of forming a linear combination of its inputs has access to that information. Linear combinations of signals from electrode arrays reveal information latent in the subspace spanned by multichannel LFP recordings and are justified by the fact that the observations themselves are linear combinations of neural sources.

Dynamics of phase-independent spectro-temporal tuning in primary auditory cortex of the awake ferret

Tuning of cortical neurons is often measured as a static property, or during a steady-state regime, despite a number of studies suggesting that tuning depends on when it is measured during a neuron's response (e.g., onset vs. sustained vs. offset). We have previously shown that phase-locked tuning to feature transients evolves as a dynamic quantity from the onset of the sound. In this follow-up study, we examined the phase-independent tuning during feature transients. Based on previous results, we hypothesized phase-independent tuning should evolve on the same timescale as phase-locked tuning. We used stimuli of constant level, but alternating between flat spectro-temporal envelope and a modulated envelope with well-defined spectral density and temporal periodicity. This allowed the measure of changes in tuning to novel spectro-temporal content, as happens during running speech and other sounds with rapid transitions without a confounding change in sound level. For 95% of neurons, tuning changed significantly from the onset, over the course of the response. For a majority of these cells, the change occurred within the first 40ms following a feature onset, often even around 10-20ms. This solidifies the idea that tuning can change rapidly from onset tuning to the sustained, steady-state tuning.

Patterned tone sequences reveal non-linear interactions in auditory spectrotemporal receptive fields in the inferior colliculus

Linear measures of auditory receptive fields do not always fully account for a neuron's response to spectrotemporally-complex signals such as frequency-modulated sweeps (FM) and communication sounds. A possible source of this discrepancy is cross-frequency interactions, common response properties which may be missed by linear receptive fields but captured using two-tone masking. Using a patterned tonal sequence that included a balanced set of all possible tone-to-tone transitions, we have here combined the spectrotemporal receptive field with two-tone masking to measure spectrotemporal response maps (STRM). Recording from single units in the mustached bat inferior colliculus, we found significant non-linear interactions between sequential tones in all sampled units. In particular, tone-pair STRMs revealed three common features not visible in linear single-tone STRMs: 1) two-tone facilitative interactions, 2) frequency-specific suppression, and 3) post-stimulatory suppression in the absence of spiking. We also found a correlative relationship between these nonlinear receptive field features and sensitivity for different rates and directions of FM sweeps, dynamic features found in many vocalizations, including speech. The overwhelming prevalence of cross-frequency interactions revealed by this technique provides further evidence of the central auditory system's role as a pattern-detector, and underscores the need to include nonlinearity in measures of the receptive field.

Bilateral cochlear implantation in the ferret: a novel animal model for behavioral studies

Bilateral cochlear implantation has recently been introduced with the aim of improving both speech perception in background noise and sound localization. Although evidence suggests that binaural perception is possible with two cochlear implants, results in humans are variable. To explore potential contributing factors to these variable outcomes, we have developed a behavioral animal model of bilateral cochlear implantation in a novel species, the ferret. Although ferrets are ideally suited to psychophysical and physiological assessments of binaural hearing, cochlear implantation has not been previously described in this species. This paper describes the techniques of deafening with aminoglycoside administration, surgical implantation of an intracochlear array and chronic intracochlear electrical stimulation with monitoring for electrode integrity and efficacy of stimulation. Experiments have been presented elsewhere to show that the model can be used to study behavioral and electrophysiological measures of binaural hearing in chronically implanted animals. This paper demonstrates that cochlear implantation and chronic intracochlear electrical stimulation are both safe and effective in ferrets, opening up the possibility of using this model to study potential protective effects of bilateral cochlear implantation on the developing central auditory pathway. Since ferrets can be used to assess psychophysical and physiological aspects of hearing along with the structure of the auditory pathway in the same animals, we anticipate that this model will help develop novel neuroprosthetic therapies for use in humans.

Context dependence of spectro-temporal receptive fields with implications for neural coding

The spectro-temporal receptive field (STRF) is frequently used to characterize the linear frequency-time filter properties of the auditory system up to the neuron recorded from. STRFs are extremely stimulus dependent, reflecting the strong non-linearities in the auditory system. Changes in the STRF with stimulus type (tonal, noise-like, vocalizations), sound level and spectro-temporal sound density are reviewed here. Effects on STRF shape of task and attention are also briefly reviewed. Models to account for these changes, potential improvements to STRF analysis, and implications for neural coding are discussed.

Nonlinearity of coding in primary auditory cortex of the awake ferret

Neural computation in sensory systems is often modeled as a linear system. This first order approximation is computed by reverse correlating a stimulus with the spike train it evokes. The spectro-temporal receptive field (STRF) is a generalization of this procedure which characterizes processing in the auditory pathway in both frequency and time. While the STRF performs well in predicting the overall course of the response to a novel stimulus, it is unable to account for aspects of the neural output which are inherently nonlinear (e.g. discrete events and non-negative spike rates). We measured the STRFs of neurons in the primary auditory cortex (AI) of the awake ferret using spectro-temporally modulated auditory gratings, or ripples. We quantified the degree of nonlinearity of these neurons by comparing their responses to the responses predicted from their respective STRFs. The responses of most cells in AI exhibited a squaring, nonlinear relation to the stimuli used to evoke them. Thus, the nonlinearity of these cells was nontrivial, that is it was not solely the result of spike rate rectification or saturation. By modeling the nonlinearity as a polynomial static output function, the predictive power of the STRF was significantly improved.

Lagged cells in the inferior colliculus of the awake ferret

Neurons in the primary auditory cortex (AI) encode complex features of the spectral content of sound, such as direction selectivity. Recent findings of temporal symmetry in AI predict a specific organization of the subcortical input into the cortex that contributes to the emergence of direction selectivity. We demonstrate two subpopulations of neurons in the central nucleus of the inferior colliculus, which differ in their steady-state temporal response profile: lagged and non-lagged. The lagged cells (23%) are shifted in temporal phase with respect to non-lagged cells, and are characterized by an 'inhibition first' and delayed excitation in their spectro-temporal receptive fields. Non-lagged cells (77%) have a canonical 'excitation first' response. However, we find no difference in the response onset latency to pure tone stimuli between the two subpopulations. Given the homogeneity of tonal response latency, we predict that these lagged cells receive inhibitory input mediated by cortical feedback projections.

Should spikes be treated with equal weightings in the generation of spectro-temporal receptive fields?

Knowledge on the trigger features of central auditory neurons is important in the understanding of speech processing. Spectro-temporal receptive fields (STRFs) obtained using random stimuli and spike-triggered averaging allow visualization of trigger features which often appear blurry in the time-versus-frequency plot. For a clearer visualization we have previously developed a dejittering algorithm to sharpen trigger features in the STRF of FM-sensitive cells. Here we extended this algorithm to segregate spikes, based on their dejitter values, into two groups: normal and outlying, and to construct their STRF separately. We found that while the STRF of the normal jitter group resembled full trigger feature in the original STRF, those of the outlying jitter group resembled a different or partial trigger feature. This algorithm allowed the extraction of other weaker trigger features. Due to the presence of different trigger features in a given cell, we proposed that in the generation of STRF, the evoked spikes should not be treated indiscriminately with equal weightings.

Dynamics of spectro-temporal tuning in primary auditory cortex of the awake ferret

We previously characterized the steady-state spectro-temporal tuning properties of cortical cells with respect to broadband sounds by using sounds with sinusoidal spectro-temporal modulation envelope where spectral density and temporal periodicity were constant over several seconds. However, since speech and other natural sounds have spectro-temporal features that change substantially over milliseconds, we study the dynamics of tuning by using stimuli of constant overall intensity, but alternating between a flat spectro-temporal envelope and a modulated envelope with well defined spectral density and temporal periodicity. This allows us to define the tuning of cortical cells to speech-like and other rapid transitions, on the order of milliseconds, as well as the time evolution of this tuning in response to the appearance of new features in a sound. Responses of 92 cells in AI were analyzed based on the temporal evolution of the following measures of tuning after a rapid transition in the stimulus: center of mass and breadth of tuning; separability and direction selectivity; temporal and spectral asymmetry. We find that tuning center of mass increased in 70% of cells for spectral density and in 68% of cells for temporal periodicity, while roughly half of cells (47%) broadened their tuning, with the other half (53%) sharpening tuning. The majority of cells (73%) were initially not direction selective, as measured by an inseparability index, which had an initial low value that then increased to a higher steady state value. Most cells were characterized by temporal symmetry, while spectral symmetry was initially high and then progressed to low steady-state values (61%). We demonstrate that cortical neurons can be characterized by a lag-dependent modulation transfer function. This characterization, when measured through to steady-state, becomes equivalent to the classical spectro-temporal receptive field.

Spectrotemporal receptive fields in anesthetized cat primary auditory cortex are context dependent

In order to investigate how the auditory scene is analyzed and perceived, auditory spectrotemporal receptive fields (STRFs) are generally used as a convenient way to describe how frequency and temporal sound information is encoded. However, using broadband sounds to estimate STRFs imperfectly reflects the way neurons process complex stimuli like conspecific vocalizations insofar as natural sounds often show limited bandwidth. Using recordings in the primary auditory cortex of anesthetized cats, we show that presentation of narrowband stimuli not including the best frequency of neurons provokes the appearance of residual peaks and increased firing rate at some specific spectral edges of stimuli compared with classical STRFs obtained from broadband stimuli. This result is the same for STRFs obtained from both spikes and local field potentials. Potential mechanisms likely involve release from inhibition. We thus emphasize some aspects of context dependency of STRFs, that is, how the balance of inhibitory and excitatory inputs is able to shape the neural response from the spectral content of stimuli.

Spectro-temporal sound density-dependent long-term adaptation in cat primary auditory cortex

Sensory systems use adaptive strategies to code for the changing environment on different time scales. Short-term adaptation (up to 100 ms) reflects mostly synaptic suppression mechanisms after response to a stimulus. Long-term adaptation (up to a few seconds) is reflected in the habituation of neuronal responses to constant stimuli. Very long-term adaptation (several weeks) can lead to plastic changes in the cortex, most often facilitated during early development, by stimulus relevance or by behavioral states such as attention. In this study, we show that long-term adaptation with a time course of tens of minutes is detectable in anesthetized adult cat auditory cortex after a few minutes of listening to random-frequency tone pips. After the initial post-onset suppression, a slow recovery of the neuronal response strength to tones at or near their best frequency was observed for low-rate random sounds (four pips per octave per second) during stimulation. The firing rate at the end of stimulation (15 min) reached levels close to that observed during the initial onset response. The effect, visible for both spikes and, to a smaller extent, local field potentials, decreased with increasing spectro-temporal density of the sound. The spectro-temporal density of sound may therefore be of particular relevance in cortical processing. Our findings suggest that low stimulus rates may produce a specific acoustic environment that shapes the primary auditory cortex through very different processing than for spectro-temporally more dense and complex sounds.

Perception and cortical neural coding of harmonic fusion in ferrets

This study examined the perception and cortical representation of harmonic complex tones, from the perspective of the spectral fusion evoked by such sounds. Experiment 1 tested whether ferrets spontaneously distinguish harmonic from inharmonic tones. In baseline sessions, ferrets detected a pure tone terminating a sequence of inharmonic tones. After they reached proficiency, a small fraction of the inharmonic tones were replaced with harmonic tones. Some of the animals confused the harmonic tones with the pure tones at twice the false-alarm rate. Experiment 2 sought correlates of harmonic fusion in single neurons of primary auditory cortex and anterior auditory field, by comparing responses to harmonic tones with those to inharmonic tones in the awake alert ferret. The effects of spectro-temporal filtering were accounted for by using the measured spectrotemporal receptive field to predict responses and by seeking correlates of fusion in the predictability of responses. Only 12% of units sampled distinguished harmonic tones from inharmonic tones, a small percentage that is consistent with the relatively weak ability of the ferrets to spontaneously discriminate harmonic tones from inharmonic tones in Experiment 1.

Binaural interactions shape binaural response structures and frequency response functions in primary auditory cortex

The overall purpose of this study is to examine the behavior of primary auditory cortex (AI) units in the three-dimensional stimulus space that resembles normal listening conditions, viz., level at the two ears and frequency. A binaural-level response area (LRA) is the response to a matrix of contralateral and ipsilateral stimuli presented at a single frequency. LRAs have been examined in the inferior colliculus and AI and found to be highly organized response patterns that are shaped by binaural interactions. The aggregate of LRAs across frequency is the binaural response structure (BRS), a new concept that captures unit behavior in this three-dimensional stimulus space. Since binaural interactions contribute greatly to configuring component LRAs, it is clear that binaural interactions help shape the aggregate BRS. The BRS contains the data required to generate binaural frequency response functions. The frequency range and magnitude of these functions depend on the level of the stimulus at each ear and the configuration of the BRS. Changing either level can greatly alter the binaural frequency response function. Thus, in addition to their classic role in localization, binaural interactions play a fundamentally important role in determining the frequency domain of units in AI.